Tools

The following open-source software are freely available for all. These are precious tools for any ATM researcher.


BlueSky, an open air traffic simulator

BlueSky is an open air traffic simulator provided for anybody who wants to visualize, analyze or simulate air traffic. It is commonly used to perform research on Air Traffic Management and Air Traffic Flows.

https://github.com/TUDelft-CNS-ATM/bluesky
GNU General Public License v3.0


OpenAP, Open Aircraft Performance Model and Toolkit

This repository contains all OpenAP databases and a Python implementation which facilitates data access and performance computation. It includes the following key modules:

  • openap.prop: a module for accessing aircraft and engine properties
  • openap.thrust: a module for computing aircraft thrust
  • openap.drag: a module for computing aircraft drag
  • openap.fuel: a module for computing fuel consumption
  • openap.kinematic: a utility library to access WRAP data
  • openap.traj: a module contains a set of tools related with trajectory generation

https://github.com/junzis/openap
GNU General Public License v3.0


pyModeS is a Python library designed to decode Mode-S (including ADS-B) messages. It can be imported to your python project to decode Mode S messages, or used as a standalone tool to view and save live traffic data.

https://github.com/junzis/pyModeS
http://pymodes.readthedocs.io
GNU General Public License v3.0


pyopensky, the Python interface for OpenSky Impala database with integrated pyModeS decoder

This Python library connects the pyModeS decoder and OpenSky Impala data interface. It aims at making the Enhance Mode-S information from OpenSky network more accessible for researchers. It can be used for:

  • Query and download ADS-B state vectors and raw Mode S messages from OpenSky Impala database.
  • Decode OpenSky Comm-B information automatically using pyModeS.

https://github.com/junzis/pyopensky
GNU General Public License v3.0


traffic, a toolbox for processing and analysing air traffic data

The traffic library helps working with common sources of air traffic data.

Its main purpose is to offer basic cumbersome data analysis methods commonly applied to trajectories and ATC sectors. When a specific function is not provided, the access to the underlying structure is direct, through an attribute pointing to a pandas dataframe.

The library also offers facilities to parse and/or access traffic data from open sources of ADS-B traffic like the OpenSky Network or Eurocontrol DDR files. It is designed to be easily extendable to other sources of data.

Static visualisation (images) exports are accessible via Matplotlib/Cartopy. More dynamic visualisation frameworks are easily accessible in Jupyter environments with ipyleaflet and altair; or through exports to other formats, including CesiumJS or Google Earth.

Xavier Olive,
“traffic, a toolbox for processing and analysing air traffic data”,
Journal of Open Source Software, 2019

https://github.com/xoolive/traffic
https://traffic-viz.github.io/
MIT License